Exam 20: Multiple Regression

In determining the best companies to work for, a number of variables are considered, including size, average annual pay, and turnover rate, etc. Moreover, employee surveys are conducted in order to assess aspects of the organization's culture, such as trust and openness to change. In an attempt to determine what affects turnover rate, a sample of 33 companies was randomly selected and data collected on the average annual bonus and turnover rate (%) for 2008. In addition, a questionnaire was administered to the employees of each company to arrive at a trust index (measured on a scale of 0-100). Below are the multiple regression results. a. Write out the estimated regression equation. b. Is the regression equation significant overall? Explain. c. How much of the variability in Turnover Rate is explained by the regression equation? d. State the hypotheses for testing the regression coefficient of Trust Index. Based on the results, what do you conclude? e. State the hypotheses for testing the regression coefficient of Average Annual Bonus. Based on the results, what do you conclude? f. Predict the turnover rate for a company with a trust index score of 70 and an average annual bonus of $6500. g. Comment on whether the conditions for multiple regression are satisfied based on the plots shown below.

What would the predicted National Birth Rate be in a country with a Life Expectancy of 60 years and a Literacy rate of 75?

Consider the following to answer the question(s) below: A regression was performed to predict the selling price of a yacht in thousands of dollars based on the number of rooms it had, its age (years), and its length (feet). The R2 is 68.45%. The equation is given here. Selling Price = 120.51 + 7.46 Rooms - 1.78 Age + 2.83 Length -What does the coefficient of Rooms mean in the context of the regression model?

Consider the following to answer the question(s) below: A regression was performed to predict the selling price of a yacht in thousands of dollars based on the number of rooms it had, its age (years), and its length (feet). The R2 is 68.45%. The equation is given here. Selling Price = 120.51 + 7.46 Rooms - 1.78 Age + 2.83 Length -If a yacht has 5 rooms, is 4 years old, and is 60 feet long, what would the model predict the selling price to be?

The correct alternate hypothesis for the overall model significance for this model is

Which of the following statements is true?

Which of the following statements best describes this model (using α = 0 .05)?

What affects flat panel LCD TV sales? Flat panel LCD televisions are sold through a variety of outlets such as large and small electronics stores, department stores, large discount chains and online. Sales figures (number of units) for the popular Sony Bravia were obtained for last quarter from a sample of 30 different stores. Also collected were data on the selling price and amount spent on advertising the Sony Bravia (as a percentage of total advertising expenditure in the previous quarter) at each store. Below are the multiple regression results. a. Write out the estimated regression equation. b. Is the regression equation significant overall? Explain. c. How much of the variability in Sales is explained by the regression equation? d. State the hypotheses for testing the regression coefficient of Price. Based on the results, what do you conclude? e. State the hypotheses for testing the regression coefficient of Advertising Expenditure. Based on the results, what do you conclude? f. Predict the sales for a store that sells the Sony Bravia for $2199 and spends 10% of its advertising budget on the product. g. Comment on whether the conditions for multiple regression are satisfied based on the plots shown below.

Using the estimated multiple regression model, the number of units sold on average at a store that sells the Sony Bravia for $2199 and spends 10% of its advertising budget on the product is

Consider the following to answer the question(s) below: National birth rates (births per 1,000) may be influenced by the average national life expectancy in years and the national literacy rate (% of population that can read and write). Data for 49 countries were obtained and the regression results follow. -The calculated F-statistic to determine the overall significance of the estimated multiple regression model is

At α = 0.01, we can conclude that

Consider the following to answer the question(s) below:: In determining the best companies to work for, a number of variables are considered, including size, average annual pay, and turnover rate, etc. Moreover, employee surveys are conducted in order to assess aspects of the organization's culture, such as trust and openness to change. In an attempt to determine what affects turnover rate, a sample of 33 companies was randomly selected and data collected on the average annual bonus and turnover rate (%) for 2008. In addition, a questionnaire was administered to the employees of each company to arrive at a trust index (measured on a scale of 0 -100). Below are the multiple regression results. -The correct null hypotheses for testing the regression coefficient of Trust Index is

Consider the following to answer the question(s) below: What affects flat panel LCD TV sales? Flat panel LCD televisions are sold through a variety of outlets. Sales figures (number of units) for the popular Sony Bravia were obtained for last quarter from a sample of 30 different stores. Also collected were data on the selling price and amount spent on advertising the Sony Bravia (as a percentage of total advertising expenditure in the previous quarter) at each store. Below are the results. -The calculated t-statistic to determine if amount spent on advertising is a significant independent variable in explaining Sony Bravia sales is

Based on the estimated multiple regression model, a company having a trust index score of 70 and an average annual bonus of $6500 has a predicted turnover rate of

Below is the plot of residuals versus predicted values for this estimated multiple regression model. What does the residual plot suggest?

How much of the variation in the National Birth Rate can be explained by the regression model?

Consider the following to answer the question(s) below: National birth rates (births per 1,000) may be influenced by the average national life expectancy in years and the national literacy rate (% of population that can read and write). Data for 49 countries were obtained and the regression results follow. -The calculated t-statistic to determine if literacy is a significant independent variable in explaining birth rates is

If an additional explanatory variable was added to the model, what would happen to R2?

Consider the following to answer the question(s) below:: In determining the best companies to work for, a number of variables are considered, including size, average annual pay, and turnover rate, etc. Moreover, employee surveys are conducted in order to assess aspects of the organization's culture, such as trust and openness to change. In an attempt to determine what affects turnover rate, a sample of 33 companies was randomly selected and data collected on the average annual bonus and turnover rate (%) for 2008. In addition, a questionnaire was administered to the employees of each company to arrive at a trust index (measured on a scale of 0 -100). Below are the multiple regression results. -How much of the variability in Turnover Rate is explained by the estimated multiple regression model?

Consider the following to answer the question(s) below: A regression was performed to predict the selling price of a yacht in thousands of dollars based on the number of rooms it had, its age (years), and its length (feet). The R2 is 68.45%. The equation is given here. Selling Price = 120.51 + 7.46 Rooms - 1.78 Age + 2.83 Length -Which of the following statements is true?